DataComparerLibrary 0.812

For comparing csv-files or 2d-array with csv-file.

• Introduction

• Installation

• Import statement for the DataComparerLibrary in Python

• Examples of using the DataComparerLibrary in Python

• Examples of using the DataComparerLibrary keywords in Robot Framework

• Examples comparing Actual Data with Expected Data

Introduction

The DataComparerLibrary can be used for:

• comparing csv-files or text-files

• comparing a 2d-matrix with a csv-file or text-file

• comparing a csv_file or text-file with a 2d-matrix

• comparing 2d-matrices

In case a difference between actual and expected data is found an exception wil be given. In Robot Framework the result will be set to failed. A strait comparison can be made, but the DataComparerLibrary offers also some special comparison options described beneath.

{PRESENT} With {PRESENT} in the expected data file you can make clear that data of a field of the actual data should be present. This can be helpful for fields that have constant changing values. For example generated id’s.

{EMPTY} With {EMPTY} in the expected data file you can make clear that data of a field of the actual data should be absent.

{SKIP} With {SKIP} in the expected data file you can make clear that the comparison of data of a complete or part of a field of the actual data should be skipped. This can be helpful for fields or parts of fields that have constant changing values. For example time or generated id’s.

{INTEGER} With {INTEGER} in the expected data file you can make clear that the data of a field of the actual data should be an integer. This can be helpful for fields that have constant changing integer values. For example integer id’s.

{NOW()…:….} With {NOW()} in the expected data file you can make clear that the data of a field or part of a field of the actual data should be (a part of) a date. You can let calculate the current or a date in the past or future. Calculation is based on the “relativedelta” method from Python. Also you can style the date in the format you want. This can be helpful for fields that have constant changing date values, but which date values have a fixed offset linked to the current date. At “Examples comparing Actual Data with Expected Data” you can find some examples how to use it.

Delimiter Default delimiter is “,”. You can use the option “delimiter_actual_data” and “delimiter_expected_data” to set another delimiter like “;” or “t” for tab. It is also possible to use a multi-character delimiter like “@#@”.

Installation

If you already have Python with pip installed, you can simply run:

pip install DataComparerLibrary

Import statement for the DataComparerLibrary in Python

from DataComparerLibrary.datacomparer import DataComparer

Examples of using the DataComparerLibrary in Python

Below there are some examples how to call the methods of the DataComparerLibrary in Python:

a = DataComparer
a.compare_data_files(self, actual_file, expected_file)
a.compare_data_files(self, actual_file, expected_file, delimiter_actual_data=';', delimiter_expected_data=';')
a.compare_data_files(self, actual_file, expected_file, delimiter_actual_data='@#@', delimiter_expected_data='@#@')
a.compare_data_2d_array_with_file(self, actual_2d_matrix_data_input, expected_file, delimiter_expected_data='\t')
a.compare_data_file_with_2d_array(self, actual_file, expected_2d_matrix_data_input, delimiter_actual_data=';')
a.compare_data_2d_arrays(self, actual_2d_matrix_data_input, expected_2d_matrix_data_input)

Examples of using the DataComparerLibrary keywords in Robot Framework

Below there are some examples how to call the keywords of the DataComparerLibrary in Robot Framework:

*** Settings ***
Library     DataComparerLibrary

*** Test Cases ***
Testcase_1
    Examples

*** Keywords ***
Examples
    Run Keyword And Continue On Failure  DataComparerLibrary.Compare Data Files  C:\\Users\\actual.csv   C:\\Users\\expected.csv
    DataComparerLibrary.Compare Data Files  C:\\Users\\actual.csv   C:\\Users\\expected.csv  delimiter_actual_data=;  delimiter_expected_data=;
    DataComparerLibrary.Compare Data Files  C:\\Users\\actual.csv   C:\\Users\\expected.csv  delimiter_actual_data=@#@  delimiter_expected_data=@#@
    DataComparerLibrary.Compare Data Files  C:\\Users\\actual.csv   C:\\Users\\expected.csv
    DataComparerLibrary.Compare Data 2d Array With File  ${actual_2d_matrix_data_input}  C:\\Users\\expected.csv  delimiter_expected_data=\t
    DataComparerLibrary.Compare Data File With 2d Array  C:\\Users\\actual.csv  ${expected_2d_matrix_data_input}  delimiter_actual_data=;
    DataComparerLibrary.Compare Data 2d Arrays  ${actual_2d_matrix_data_input}  ${expected_2d_matrix_data_input}

Examples comparing Actual Data with Expected Data

Below there is an example of actual and expected data with some different cases.

Based on current datetime = 2023-09-06 19:04:00 (example):

Actual csv file or 2d-array
id	name	city	start datetime	code	password
87	John	London	2019-09-01 10:00:15	abc1	xxxxxxxx
88	Bert	Amsterdam	2023/09/06 19:02:00		xxxxxxxx
89	Klaas	Brussel	23-8-6 12:04:17	5ghi	xxxxxxxx
90	Joe	Helsinki	08062025 12:04:17	99fg	xxxxxxxx

Expected csv file or 2d-array
id	name	city	start datetime	code	password
{INTEGER}	John	London	{NOW()-4Y5D:YYYY-MM-DD}	abc1	{PRESENT}
{INTEGER}	Bert	Amsterdam	{NOW():YYYY/MM/DD} {SKIP}	{EMPTY}	{PRESENT}
{INTEGER}	Klaas	Brussel	{NOW()-1M:YY-M-D} {SKIP}	5ghi	{PRESENT}
{INTEGER}	Joe	Helsinki	{NOW()+1Y9M2D:DDMMYYYY} {SKIP}	{SKIP}	{PRESENT}